Predicting optimal solution cost with bidirectional stratified sampling (abstract)

Levi H.S. Lelis; Roni Stern; Ariel Felner; Sandra Zilles; Robert C. Holte

Predicting optimal solution cost with bidirectional stratified sampling (abstract)

Levi H.S. Lelis, Roni Stern, Ariel Felner, Sandra Zilles, Robert C. Holte

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Optimal planning and heuristic search systems solve state-space search problems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i.e., without actually finding a solution path of that cost. We present an efficient algorithm, BiSS, based on ideas of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. Our method is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity.

Original language	English
Title of host publication	Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012
Pages	186-187
Number of pages	2
State	Published - 2012
Externally published	Yes
Event	5th International Symposium on Combinatorial Search, SoCS 2012 - Niagara Falls, ON, Canada Duration: 19 Jul 2012 → 21 Jul 2012

Publication series

Name	Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012

Conference

Conference	5th International Symposium on Combinatorial Search, SoCS 2012
Country/Territory	Canada
City	Niagara Falls, ON
Period	19/07/12 → 21/07/12

Cite this

@inproceedings{e46babeb070c463094823fd33d5e1546,

title = "Predicting optimal solution cost with bidirectional stratified sampling (abstract)",

abstract = "Optimal planning and heuristic search systems solve state-space search problems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i.e., without actually finding a solution path of that cost. We present an efficient algorithm, BiSS, based on ideas of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. Our method is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity.",

author = "Lelis, {Levi H.S.} and Roni Stern and Ariel Felner and Sandra Zilles and Holte, {Robert C.}",

year = "2012",

language = "אנגלית",

isbn = "9781577355847",

series = "Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012",

pages = "186--187",

booktitle = "Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012",

note = "5th International Symposium on Combinatorial Search, SoCS 2012 ; Conference date: 19-07-2012 Through 21-07-2012",

}

Lelis, LHS, Stern, R, Felner, A, Zilles, S & Holte, RC 2012, Predicting optimal solution cost with bidirectional stratified sampling (abstract). in Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012. Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012, pp. 186-187, 5th International Symposium on Combinatorial Search, SoCS 2012, Niagara Falls, ON, Canada, 19/07/12.

Predicting optimal solution cost with bidirectional stratified sampling (abstract). / Lelis, Levi H.S.; Stern, Roni; Felner, Ariel et al.
Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012. 2012. p. 186-187 (Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Holte, Robert C.

PY - 2012

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N2 - Optimal planning and heuristic search systems solve state-space search problems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i.e., without actually finding a solution path of that cost. We present an efficient algorithm, BiSS, based on ideas of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. Our method is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity.

AB - Optimal planning and heuristic search systems solve state-space search problems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i.e., without actually finding a solution path of that cost. We present an efficient algorithm, BiSS, based on ideas of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. Our method is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity.

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BT - Proceedings of the 5th Annual Symposium on Combinatorial Search, SoCS 2012

T2 - 5th International Symposium on Combinatorial Search, SoCS 2012

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Predicting optimal solution cost with bidirectional stratified sampling (abstract)

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